On successful requests, guardrail evaluations run and store results in
request_data["litellm_metadata"]["standard_logging_guardrail_information"],
but the spend-log serialization reads from request_data["metadata"], so
guardrail evaluations were never reported in Request Logs.
The failure path already had this transfer; this adds the same logic to
the success path so guardrail evaluation info appears in both success
and failure spend logs.
Fixes LIT-6314.
* fix(auth): quiet malformed virtual key rejections to stdout
Reduce noisy invalid-api-key error logs by classifying malformed virtual
keys and routing their rejections to stdout as WARNING instead of stderr
as ERROR. Suppressible via LITELLM_LOG=ERROR or log_client_error_tracebacks=true.
Changes:
- auth_utils: is_invalid_virtual_key_error() classifier and marker functions
- auth_exception_handler: log invalid keys as WARNING to child logger before
identity seeding and callbacks, escalate non-401 transforms to ERROR
- user_api_key_auth: websocket early-raise WebSocketException(1008) to avoid
double-logging at HTTP layer
- _logging: child logger verbose_proxy_stdout_logger with no handler/level;
LevelRoutingStreamHandler routes its WARNING records to stdout; handler
setLevel in _turn_on_json() closes JSON config handler level leak
- test_auth_exception_handler: new test case verifying malformed-key logs
at WARNING with marker retention through transformations
Fixes LIT-5362
* fix(auth): classify malformed-key 401 by raise-site marker, not message text
Review round 1 (Greptile P2, veria Low):
- Move the marker attribute name to litellm/constants.py per the shared
sentinel convention
- Stamp the marker on the malformed-key 401 where it is raised and classify
only by it. Message text is caller-influenceable on other 401s (vector
store ids, organization ids are interpolated into their messages), so a
phrase match would let a request body demote an authorization failure to
the quiet log path
- Regression test: a 401 carrying the phrase but not the marker stays at
ERROR on stderr
Shadow eval jobs previously targeted only virtual keys, so deployments on
pure JWT auth (which present no key at all) could never sample their
traffic. Jobs now carry a typed (target_type, target_id) pair covering
keys, teams, and users; sampling matches the identity every request
resolves to at auth time, so team and user jobs cover JWT traffic with
no client changes.
Resolves LIT-6578
The batch start told the seed which LiteLLM_SpendLogs rows were its own, but
using it as a hard cutoff also dropped rows another pod had already persisted.
Those rows are only repaid by that pod's own increment, so if it died first the
window row stayed permanently under the recorded spend.
The seed now reads both sums in one scan and takes off this batch's own spend,
flooring at the pre-batch total for the case where its log rows have not landed
yet. Redis payloads keep an empty request_ids so a leader from before the field
was dropped can still merge what it pops during a rolling deploy.
Claude-Session: https://claude.ai/code/session_01QvQzYztinxj8ZuD5YxbVdL
precached_prompt_tokens is a subset of prompt_tokens (OpenAI cached_tokens
semantics), so map it to prompt_tokens_details.cached_tokens instead of
adding it on top of prompt/total. Emit stream usage from any final chunk
carrying it rather than only finish_reason stop, which dropped tokens for
function_call and length streams. Merge auth metadata into a new dict in
the gigachat router handler instead of mutating the shared parsed-body
cache in place.
- sync llm_passthrough_route: read and close an error-status streaming
response before mapping it, so upstream 4xx/5xx surface as the provider
error instead of httpx.ResponseNotRead
- AsyncPassthroughStreamingResponse: expose aiter_bytes() and carry
_hidden_params so the router attaches headers in place instead of
wrapping the stream in HiddenParamsAsyncIteratorWrapper, which 500'd
every streaming azure router-model passthrough request
- logging: swap the passthrough httpx result for the transformed
ModelResponse/EmbeddingResponse when firing success callbacks
- get_llm_provider: resolve gigachat from its api base and drop the dead
gigachat_models elif branch
- constants: register the gigachat api base in openai_compatible_endpoints
* feat(spend_tracking): persist router metadata in spend logs for internal router models
* test(spend_tracking): expect router_metadata key in exact-payload tests, type the routed-kwargs helper
The chat-to-Responses reverse transform kept only text blocks, so an image
input was dropped before the count went to OpenAI. A 256x256 image request
counted 13 tokens instead of 268.
/v1/responses/input_tokens returned 200 with a count for an empty
"input" ("" or []), while OpenAI returns a 400 missing_required_parameter.
The route also went through optimistic budget reservation, which is only
released by LLM success/failure callbacks that a token count never
reaches, so every call leaked a reservation until TTL expiry and could
429 real traffic. Both routes plus the /openai alias now join
/utils/token_counter in the reservation exemption set.
* fix(proxy): deliver budget alerts on webhook-only alerting and accept ALERTING_WEBHOOK_URL
ProxyLogging.budget_alerts forwarded to the alerting pipeline only when
'slack' was in general_settings.alerting, so alerting: ['webhook'] plus
WEBHOOK_URL silently never delivered a budget alert (the config
/health/services?service=webhook exists to test). Forward when 'webhook'
is present too; SlackAlerting.send_alert already fans out per channel.
Also accept a provider-neutral ALERTING_WEBHOOK_URL env fallback for the
Slack-format channel (any Slack-compatible receiver works), mark it as a
sensitive var, and de-brand the admin UI alerting copy.
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(ui): format settings.tsx with prettier
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* chore(ui): regenerate schema.d.ts for updated alerting description
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* ci: retrigger checks after ALERTING_WEBHOOK_URL docs merged
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---------
Co-authored-by: yassin <yassin@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Default remains true so lite claude turns tool search back on through
a proxy. An explicit false or auto in the env or settings is left alone
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
Claude Code turns tool search off when ANTHROPIC_BASE_URL is a proxy.
lite claude, lite up, login --config-claude, and autoroute now force
ENABLE_TOOL_SEARCH=true so MCP tools stay deferred through the proxy
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
- forward unrouted /gigachat/* requests with env credentials like other passthrough providers (the old fallback returned 400 on any request without a routed model, /gigachat/models included)
- fix basedpyright budget breaches across the gigachat provider, common_request_processing, and llm_passthrough_endpoints with real narrowing, no new suppressions
- add regression tests for the fallback target, auth header, and model-less endpoints
The route-level regression test returns a real prisma row from a mocked
update and asserts both routes serialize it to a 200 with the toggled
blocked flag, which is exactly the path that raised AttributeError before
the validator guard. Also binds the loop variable in the e2e poll lambda
(ruff B023).
The one-time seed for a budget window row subtracted the batch's own
LiteLLM_SpendLogs rows by request_id, and request_id is the client's
x-litellm-call-id whenever the response carries no id of its own. Carrying
that set through the queue meant an unbounded, client-controlled aggregate
that the commit-failure requeue kept alive across retries.
Every log row at or after a batch's earliest start is owed by an increment
that still reaches the row, so summing only rows before it needs nothing
from the request. That drops request_ids end to end and closes the
cross-pod double count the id list could not see.
#34940 widened the mask-in-place safety guard so a Responses-API
`instructions` field (and a combined messages+input body) skips the
PII masking branch. With `on_flagged: "monitor"` that fell straight
through to "allow", so PII that used to be masked now reaches the
model unredacted.
Monitor means "don't block", not "don't redact". Recover the one shape
whose payload is still fully writable: mask it and write the redacted
instructions back into `data["instructions"]` directly, since
apply_redacted_messages_back has no path for that field and would
otherwise fold the instructions text into `data["input"]`.
The combined messages+input and multimodal shapes stay unmasked - both
are unsafe to write back, not merely unwritable - and now log an error
naming the reason instead of passing silently.
No block/allow decision changes: block and inject_system_message keep
the exact outcomes #34940 shipped.
Direct access on /model/info was read from the user record alone, so an
unrestricted user calling with a key limited to a few models saw every non-team
deployment, including ones the key gets a 403 on. Resolve the key's grant the
same way and intersect the two.
Resolving a grant now also expands access groups, which the key path needs and
the user path was missing.
Claude-Session: https://claude.ai/code/session_01XL7LBFEew4wi8gphVCDq6n
Model access group budgets shipped API-only, so the only way to give a group a
budget was a curl. Adds an Access Group Budgets tab under Models & Endpoints
that lists every group with the spend drawn against its shared pool, and a
modal to set, edit or clear the budget.
/access_group/list now carries each group's budget and spend inline, so the
table renders from one read instead of one follow-up request per row.
